We propose the integration of two powerful technologies: molecular genetics and functional analysis, to facilitate identification genes which contribute to important biological problems. The focus of this study is genes that dysregulate glucose homeostasis by impairing insulin sensitivity and beta cell function. This dysregulation results in diabetes and other common disorders. Molecular genetics and functional biology individually have great strengths, but also countervailing limitations. Importantly, these strengths and weaknesses are cross-compensating. We propose to combine the strengths to develop an integrated system for gene discovery. This will be achieved by testing this integration strategy in two different scenarios faced by investigators searching for genes that contribute to human disorders. In Aim 1 there is extensive molecular genetic evidence for genes contributing to acute insulin response and disposition index on chromosome 11q in the IRAS Family Study, but to date we have no complementary functional biology studies. We will use RNAi technology to systematically knock down genes prioritized from prior molecular genetic analysis to identify candidates for involvement in acute insulin response and disposition index. In Aim 2 we will use the knock down technology to assess genes identified by Genome Wide Association analysis in the IRASFS. In this Aim we will knock down H150 genes which have identified in GWAS analysis of acute insulin response, insulin resistance, and disposition index using various knockdown models. Aim 3 will expand the molecular genetic and functional analysis on the subset of genes identified in Aims 1 to 3. This will include intense resequencing of genes and functionally assessing specific alleles, or combinations of alleles. The goals of this study are both the scientific identification of genes important in glucose homeostasis and diabetes and, second, the technical demonstration that integrated molecular genetic and functional analysis can be translated into substantial savings in time, labor, and materials. PUBLIC HEALTH RELEVANCE: We propose to integrate the use of two technologies, molecular genetics and functional analysis, to accelerate the identification of genes contributing to insulin sensitivity and pancreatic beta cell function.